无论是定制百万流量的网页广告，还是提高小餐馆的库存效率，数据的作用变得越来越显而易见。曾几何时，我们 不知道如何通过数据挖掘找提升业务效率的办法。 但在这个课程中，你会了解到到什么是数据，什么是能够通过数据挖掘解决的问题 — 当然也可能你从来没有研究过这些。 你会了解到到如何通过现有的数据进行一个问题的研究，找到各种变量、变量之间的关系、及基础的统计学和如何清晰得展示你的研究结果。 在完成这门课程之后，你将能够运用强大的数据分析工具 － 类似SAS或Python － 来管理和可视化你的数据，以及如何应对数据丢失、组合的变化和图表处理等问题。 同时，通过这门课程，你可以和大家一起分享你的所学并获得反馈，也能够了解你的同伴们是如何运用数据解决他们的问题。
Welcome Video
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来自 Wesleyan University 的课程
数据管理与可视化
653 个评分
从本节课中
Selecting a research question
We would like to welcome you to Wesleyan University's Data Analysis and Interpretation Specialization. In this session, we will discuss the basics of data analysis. Your task will be to select a data set that you would like to work with and to review available code books that help you develop your own research question. You will also set up a Tumblr blog that will allow you to reflect on these experiences, submit assignments and share your work with others throughout the course. First, you may want to check out the welcome video
与讲师见面
Lisa DierkerProfessor
Psychology
I agree. >> Each country would have a specific HIV
number and now you're not looking at the right country, so does that make sense?
>> I see.
Yes, but it's hard for me to articulate what you just said.
>> You are embarking on a journey.
Perhaps your goals and directions are clear.
[MUSIC]
Perhaps you have some broad ideas and passion to guide you through your studies.
[NOISE] Whatever your journey, you can be certain that it is unique.
No one else will follow exactly the same path.
Perhaps you're an entrepreneur with innovative ideas for
products and services.
Perhaps you're seeking a deeper understanding of our universe
through science.
[MUSIC]
Perhaps you're interested in understanding the behavior of individuals,
communities, or societies.
Or perhaps you're passionate about change, about making the world a better place.
Whatever your passion, you can be sure that your journey is unique and
yet, you're united by the need to analyze, understand, and describe data.
Many students view the development of skills involved in analyzing data
as an obstacle to be overcome on their journey.
Rather than an obstacle,
data analysis skills actually provide a common language that will speed you along.
You'll need this language in order to understand what others are saying and
to tell your story.
That's why this specialization was created.
In each course, we'll present statistical and
machine learning tools allowing you to analyze and
interpret large datasets in the service of your own research questions.
Throughout the specialization, you'll be conducting original research,
asking original questions, and communicating your methods and results.
This is not an academic exercise but rather an opportunity to create new
knowledge and to share this understanding with others.
It's an opportunity to further your passion.
>> In the future, I think it's gonna be really important that we find this
subsurface ice to sustain astronauts who may explore Mars one day.
>> HIV rate is not significantly correlated to life expectancy
in Latin American countries.
However, it is significantly correlated in the lowest income group.
>> What sets apart the behavior of binge drinkers from people who drink casually,
who drink more moderately?
>> The total mean of drug usage that was reported by adolescents show that most
people were not using drugs.
>> This specialization grew out of our National Science Foundation
funded Passion-Driven Statistics project.
It represents a hands-on project-based approach aimed at getting you working
you actively on a research question of your choosing from the very beginning.
>> The specialization is designed for
students who are interested in developing skills for working with data and
using statistical and machine learning tools to analyze them.
Absolutely no prior experience with data is required.
>> Throughout the specialization, you'll be working with data that already exists.
We've chosen a number of datasets that contain vast amounts of information
covering drug use, adolescent health, space science and more.
From these datasets you'll be able to pose questions of interest to you and
then turn raw data into useful information.
>> Although our goal is ultimately to present materials across several
major platforms used to conduct data analysis,
we'll begin with the opportunity to learn either Python or SAS.
Both provide outstanding data analysis tools for
modern computing with large datasets.
To help you decide which you'd like to learn, or
at least learn first, we provided a document comparing system requirements and
other similarities and differences.
>> Whichever you choose, you'll be writing and running your own programs.
For some of you who've never written code before, this may seem daunting but
don't worry because there's lots of support.
Remember, this is data analysis in the service of research questions,
your research question always comes first.
Finally, you will have the opportunity to use the data analysis skills
to work with our industry partner to complete a capstone data analysis project
that addresses an important issue in society.
When you're done, you will have a high quality report that you can show to
professionals and potential employers to demonstrate the skills you've learned.
>> Throughout this specialization, we'll not only get you working with a range of
statistical and machine learning tools but we'll also get you telling your story, and
developing the skills necessary to communicate your findings to both expert
and novice audiences.
We encourage you to join in the discussions, where you'll find answers to
many of your questions, and get both instructor and peer support.
Enjoy.
>> You find out what pertains to you.
You have to figure out what you're genuinely interested in.
>> If it's something's that's yours,
something you can relate to, there's more of you that goes into it.
>> Each student can look at the same dataset but come up with a different
research question and they can choose to analyze it in a different way and
where they take that is completely their own.
Data is just so awesome and
I really want students to see that, I want them to experience it.
I want them to embrace it and so I just want them to understand that they can
take this with them for the rest of their life and it's always going to be valuable.
>> This has changed the way that I view the world,
this changes the way that I hear about research and literature.
It changes everything.
